Method and system for assessing hazard risks associated with geographical locations

ABSTRACT

A method and a system for assessing hazard risks associated with geographical locations are provided. The server receives information associated with a geographical location from a user device. The server identifies a hazard associated with the geographical location based on the historical hazard data. The server retrieves one or more files associated with the hazard. The server determines a first risk score for the geographical location based on at least the one or more files or a first set of rules associated with the hazard. The server determines a second risk score for the geographical location based on at least the one or more files or a second set of rules associated with the hazard. The server determines the second risk score when a criterion associated with the hazard is met. The server communicates at least one of the first risk score or the second risk score to a user.

FIELD OF THE INVENTION

The present invention relates generally to assessing risks, and moreparticularly, to a method and a system for assessing hazard risksassociated with geographical locations.

BACKGROUND

Hazards, both natural and man-made, have led to severe damages to humanlife and property. Examples of such hazards include floods, fire fromany cause, a hailstorm, a tornado, a hurricane, an earthquake,radiations from radioactive zones and nuclear power plants, a landslide,volcanic eruptions, brownfield or superfund sites, crime, and the like.Hazards may affect specific geographical locations due to risk caused byenvironmental conditions or man-made offences. Therefore, it has becomeparamount for an individual seeking to buy, move in, or rent a propertyin an area to assess a hazard risk associated with the area.

Traditionally, hazard risk scores are determined to assess hazard risksfor the property. The hazard risk scores are determined by whether theproperty is inside or outside a hazard risk zone that is likely to beaffected by a hazard. This is done by performing a geospatial operationon a geospatial file. The geospatial file includes depiction of varioushazards in form of geospatial elements such as polygons, lines, points,or raster cells in a map of a geographical area such as a country or astate. For example, to determine a flood risk for a property, apoint-in-polygon (PIP) operation, i.e., geospatial operation isperformed on the geospatial file that depicts a geographical area in theform of polygons. Each polygon of the geographical area is classifiedinto a hazard (flood) risk zone such as a high risk zone, a moderaterisk zone, or a low risk zone. Based on the hazard risk zone, a hazardrisk score is associated with each polygon. The point-in-polygon (PIP)operation identifies a polygon in which the property is located andoutputs the hazard risk score of the identified polygon as the hazardrisk score of the property. Thus, the hazard risk score of the propertyis determined based on a single factor, i.e., whether the property is inthe high risk zone, the moderate risk zone, or the low risk zone. Sincethe determination of the hazard risk score is based on a single factor,the information obtained is insufficient to thoroughly assess the hazardrisk associated with the property. Thus, the hazard risk score obtainedby the abovementioned method does not yield accurate results and wouldlead an individual into a false sense of security.

The traditional methods further determine the hazard risk scores for thepolygons beforehand and embed it in the geospatial file. When a hazardrisk assessment for the geographical location or the property isrequested by the individual, the hazard risk score of the polygonassociated with the geographical location or the property is obtainedfrom the geospatial file and provided to the individual. As the hazardrisk scores are determined beforehand, they do not depict real time dataand hence lead to inaccurate assessment of the hazard risks. Further, toinclude any additional data in the geospatial file, the geospatial filehas to be rebuilt with new hazard risk scores.

In light of the foregoing, there exists a need for a technical and morereliable solution that provides a method of assessing hazard risksassociated with the geographical location that improves the accuracy ofthe risk scores, relies on more than one factor, and solves theaforementioned problems of the traditional methods.

SUMMARY

Various embodiments of the present invention provide a method and asystem for assessing hazard risks associated with geographicallocations. The method includes multiple operations that are executed bya server of the system to assess the hazard risks associated with thegeographical locations. The server receives information associated witha geographical location from a user device over a communication network.The information includes at least an address or a geographical positionof the geographical location. The server identifies a hazard associatedwith the geographical location. The server identifies the hazard basedon the historical hazard data. The hazard includes natural or man-madehazards. The server retrieves the historical hazard data from a memory.The server further retrieves one or more files associated with thehazard from the memory. The one or more files include a plurality ofgeospatial elements. The plurality of geospatial elements includes atleast lines, points, polygons, or raster cells.

The server determines a first risk score for the geographical locationbased on at least the one or more files or a first set of rulesassociated with the hazard. The server further determines a second riskscore for the geographical location. The server determines the secondrisk score based on at least the one or more files or a second set ofrules associated with the hazard. The server determines the second riskscore when a criterion associated with the hazard is met. The criterionassociated with the hazard is based on at least the first risk score orthe one or more files. The server communicates at least one of the firstrisk score or the second risk score associated with the geographicallocation to a user. The first and second risk scores indicate a level ofseverity of the hazard for the geographical location. The servercommunicates the first risk score to the user when the criterionassociated with the hazard is unmet.

The server further determines a third risk score for the geographicallocation. The server determines the third risk score based on at leastthe one or more files or a third set of rules associated with thehazard. The server determines and communicates the third risk score whenthe criterion associated with the hazard is unmet. Thus, the method andthe system of the present invention improve an accuracy of the riskscores by considering multiple factors while determining the risk scoresassociated with the geographical locations. Further, the method and thesystem of the present invention determine the risk scores on-the fly,i.e., dynamically, and do not rely on predetermined risk scores.

BRIEF DESCRIPTION OF THE DRAWINGS

The accompanying drawings illustrate the various embodiments of systems,methods, and other aspects of the invention. It will be apparent to aperson skilled in the art that the illustrated element boundaries (e.g.,boxes, groups of boxes, or other shapes) in the figures represent oneexample of the boundaries. In some examples, one element may be designedas multiple elements, or multiple elements may be designed as oneelement. In some examples, an element shown as an internal component ofone element may be implemented as an external component in another, andvice-versa.

FIG. 1 illustrates an environment for assessing hazard risks associatedwith geographical locations in which various embodiments of the presentinvention are practiced;

FIG. 2 is a block diagram that illustrates various components of a userdevice and a server of the environment of FIG. 1, in accordance with anembodiment of the present invention;

FIGS. 3A and 3B, collectively, are a flow chart that illustrate a methodfor assessing a hazard risk associated with a geographical location, inaccordance with an embodiment of the present invention;

FIGS. 4A and 4B, collectively, are a flow chart that illustrate a methodfor assessing a flood risk associated with a geographical location, inaccordance with an embodiment of the present invention;

FIG. 5 is a flow chart that illustrates a method for assessing the floodrisk associated with a geographical location, in accordance with anotherembodiment of the present invention;

FIGS. 6A, 6B, and 6C, collectively, are a flow chart that illustrate amethod for assessing a wildfire risk associated with a geographicallocation, in accordance with an embodiment of the present invention; and

FIG. 7 is a block diagram that illustrates a computer system forassessing the hazard risks associated with the geographical locations,in accordance with an embodiment of the present invention.

Further areas of applicability of the present invention will becomeapparent from the detailed description provided hereinafter. It shouldbe understood that the detailed description of exemplary embodiments areintended for illustration purposes only and are, therefore, not intendedto necessarily limit the scope of the invention.

DETAILED DESCRIPTION

As used in the specification and claims, the singular forms “a”, “an”and “the” may also include plural references. For example, the term “anarticle” may include a plurality of articles. Those with ordinary skillin the art will appreciate that the elements in the figures areillustrated for simplicity and clarity and are not necessarily drawn toscale. For example, the dimensions of some of the elements in thefigures may be exaggerated, relative to other elements, in order toimprove the understanding of the present invention. There may beadditional components described in the foregoing application that arenot depicted on one of the described drawings. In the event such acomponent is described, but not depicted in a drawing, the absence ofsuch a drawing should not be considered as an omission of such designfrom the specification.

Before describing the present invention in detail, it should be observedthat the present invention utilizes a combination of system components,which constitutes systems and methods for assessing hazard risksassociated with geographical locations. Accordingly, the components andthe method steps have been represented, showing only specific detailsthat are pertinent for an understanding of the present invention so asnot to obscure the disclosure with details that will be readily apparentto those with ordinary skill in the art having the benefit of thedescription herein. As required, detailed embodiments of the presentinvention are disclosed herein; however, it is to be understood that thedisclosed embodiments are merely exemplary of the invention, which canbe embodied in various forms. Therefore, specific structural andfunctional details disclosed herein are not to be interpreted aslimiting, but merely as a basis for the claims and as a representativebasis for teaching one skilled in the art to variously employ thepresent invention in virtually any appropriately detailed structure.Further, the terms and phrases used herein are not intended to belimiting but rather to provide an understandable description of theinvention.

References to “one embodiment”, “an embodiment”, “another embodiment”,“yet another embodiment”, “one example”, “an example”, “anotherexample”, “yet another example”, “for example” and so on, indicate thatthe embodiment(s) or example(s) so described may include a particularfeature, structure, characteristic, property, element, or limitation,but that not every embodiment or example necessarily includes thatparticular feature, structure, characteristic, property, element orlimitation. Furthermore, repeated use of the phrase “in an embodiment”does not necessarily refer to the same embodiment.

Hazards are naturally occurring events and man-made activities that havea potential to cause damage to humans and property. Hazards include, butare not limited to, flooding, coastal storm surge, tsunami, wildfire,fire from any cause, damaging wind, hailstorm, tornado, lightningstrikes, hurricane, earthquake, fracking induced earthquake, radiationsfrom radioactive zones and nuclear power plants, wind borne debris,landslide, lava flow, volcanic eruptions, brownfield or superfund sites,leaking of underground storage tanks, and crime. Hereinafter, variousmethods of assessing the hazard risks for the geographical locationshave been described that will become apparent to a person havingordinary skill in the relevant art.

Referring now to FIG. 1, an environment 100 for assessing hazard risksassociated with geographical locations in which various embodiments ofthe present invention are practiced is shown. The environment 100assesses the hazard risks on-the-fly, i.e., dynamically, as disclosedherein. The environment 100 includes a user device 102 and a server 104that communicate with each other by way of a communication network 106.Examples of the communication network 106 include, but are not limitedto, a wireless fidelity (Wi-Fi) network, a light fidelity (Li-Fi)network, a satellite network, the Internet, a mobile network such as acellular data network, high speed packet access (HSPA), or anycombination thereof.

The user device 102 is a computing device that is used by a user toperform various activities. The user uses the user device 102 to obtainhazard risks for a geographical location. In an embodiment, the userdevice 102 transmits the geographical location to the server 104 bymeans of a service application installed on the user device 102 or a webpage hosted by the server 104 which is accessed on the user device 102.To obtain the hazard risks, the user inputs information associated withthe geographical location such as an address or a geographical position,i.e., latitude and longitude, by means of the service application or theweb page. In another embodiment, the server 104 receives the address orthe geographical position based on the current geographical location ofthe user device 102 over the communication network 106. In yet anotherembodiment, the user transmits a set of geographical locations. In oneembodiment, the user transmits the set of geographical locations to theserver 104 by submitting an electronic database of addresses by way ofan Application Programming Interface (API) or a Batch processingInterface (BPI).

The user device 102 further displays a risk score, including first andsecond risk scores, for the geographical location. The risk scoreindicates a level of severity of the hazard. The risk score can bequalitative or quantitative. In an embodiment, the risk scores arealphabets, for example an ‘A’ indicating that the geographical locationis least likely to be affected by the hazard, a ‘B’ indicating that thegeographical location is less likely to be affected by the hazard, a ‘C’indicating that the geographical location is moderately likely to beaffected by the hazard, a ‘D’ indicating that the geographical locationis more likely to be affected by the hazard, and an ‘F’ indicating thatthe geographical location is most likely to be affected by the hazard.In another embodiment, the first and second risk scores are numerals,for example ‘0’ indicating that the geographical location is leastlikely to be affected by the hazard and ‘14’ indicating that thegeographical location is most likely to be affected by the hazard.Examples of the user device 102 include, but are not limited to, apersonal computer, a laptop, a smartphone, a tablet, a phablet, apersonal digital assistant (PDA), and the like. The user device 102 hasbeen described in detail in conjunction with FIG. 2.

The server 104 is a computing device, a network of computers, a softwareframework, or a combination thereof, that may provide a generalizedapproach to create the server implementation. In an embodiment, theoperation of the server 104 may be dedicated to execution of procedures,such as, but not limited to; programs, routines, or scripts stored inone or more memories for supporting its applied applications. Examplesof the server 104 include, but are not limited to, a personal computer,a laptop, or a network of computer systems. The server 104 may berealized through various web-based technologies such as, but not limitedto, a Java web-framework, a .NET framework, a PHP framework, or anyother web-application framework. The various operations of the server104 have been described in detail in conjunction with FIGS. 2-6.

The server 104 determines historical hazard data for the geographicallocation by taking into consideration the natural and man-made hazardsthat have occurred and level of damages caused due to the hazards at thegeographical location in the past. The server 104 further stores it in amemory (shown in FIG. 2). In an embodiment, the server 104 receives thehistorical hazard data from a global database or a regional database andstores it in the memory. In another embodiment, the server 104 receivesthe historical hazard data from a remote server (not shown). The server104 further considers the hazards and the level of damages caused due tothe hazards to the geographical areas that are in the vicinity of thegeographical location. In an example, for a geographical location ‘R’,the server 104 determines the historical hazard data for thegeographical location ‘R’. The historical hazard data may includeinformation about a Storm ‘S’ that occurred in the year ‘X’ and thedamage caused due to the storm, Hurricane ‘T’ that caused flooding inthe year ‘Y’ and the level of damage caused by the Hurricane ‘T’, andany other natural or man-made hazards that have occurred in thegeographical location ‘R’. Thus, the server 104 identifies ‘storm’ and‘hurricane’ as the hazards associated with the geographical location‘R’. The server 104 further considers the hazards and the level ofdamages caused in areas ‘U’ and ‘V’ that are in the vicinity of thegeographical location ‘R’. Thus, to determine the hazard associated withthe geographical location ‘R’, the server 104 retrieves the historicalhazard data when the server 104 receives the geographical location ‘R’by way of the communication network 106.

The server 104 stores a set of files (such as geospatial files) thatinclude first through third files that are associated with the hazard inthe memory. The set of files include geographical areas and depiction ofhazards in a form of geospatial elements such as polygons, lines,points, or raster cells. In an example, for hazards such as floods, thegeospatial files include a geographical area that is divided intopolygons where each polygon indicates a flood risk zone. In anotherexample, the geographical area is divided into raster cells where eachraster cell indicates a hazard risk zone. To determine hazards such asfire, the geographical area may include points to depict objects such asfire hydrant points. Further for hazards such as earthquakes, earthquakelines are depicted on the geographical area to indicate the probabilityof occurrence of earthquakes. The server 104 stores data (includingfirst and second data) associated with the geospatial files that mayinclude, but not be limited to risk values or distance between twopoints in a geospatial file in the memory. The server 104 further storessets of rules (that include first through third sets of rules)associated with each hazard in the memory. Thus, when the server 104identifies the hazard based on the historical hazard data, the server104 retrieves the associated set of files and the sets of rules todetermine the risk score for the hazard. In an example, the server 104receives a geographical location ‘G’ from the user device 102. Theserver 104 identifies three hazards, i.e., tsunami, fire, and crime,which are associated with the geographical location ‘G’. To determinethe risk score associated with the hazard ‘tsunami’, the server 104retrieves the set of files associated with tsunami. The first file maydepict coastal lines in a geographical area that includes thegeographical location ‘G’. Further, the second file may depict thegeographical area in the form of tsunami zones such that each tsunamizone indicates a tsunami risk associated with the tsunami zone.

The server 104 performs a first set of geospatial operations on thefirst file to extract the first data from the memory. The first set ofgeospatial operations may include, but are not limited to, apoint-in-polygon (PIP) operation, a distance-to-line (DTL) operation, adistance-to-point (DTP) operation, a drive-time-time (DTT) operation,and a drive-time-distance (DTD) operation. The PIP operation checks ifthe geographical location lies in a polygon and identifies the polygonto obtain information such as risk value associated with the polygon.The DTL operation is performed on a geospatial file (that includeshazards depicted in the form of lines) to determine a distance between ageographical location and a line. The DTP operation is performed on ageospatial file that includes points (in an example, objects such asfire hydrant points) to determine a distance between a geographicallocation and a point. Similarly, the DTT operation is performed on ageospatial file that includes points to determine a drive-time betweentwo points (such as objects, locations, and the like). The DTD operationis performed on a geospatial file that includes points to determine adrive distance between two points. The first data includes informationassociated with the geographical location and the hazard such as riskvalues, distances between the geographical locations and geospatialelements, and the like. The server 104 determines the first risk scorebased on the first data and the first set of rules associated with thehazard. In the example, the server 104 performs the DTL operation on thefirst file to obtain the distance between the geographical location anda nearest coast line. The server 104 determines the first risk scorebased on the first data, i.e., the distance, and the first set of rulesthat are associated with ‘tsunami’. The first set of rules dictate thatif the geographical location is within 20 miles from a coast, the firstrisk score is one of ‘C’, ‘D’, or ‘F’ and if the distance is more than20 miles from the coast, the first risk score is one of ‘A’ or ‘B’.

To improve an accuracy of hazard risk assessment, the server 104 furtherinitiates a criterion associated with the hazard. In an example, thecriterion includes an additional factor associated with the hazard to beconsidered while determining the first risk score. In another example,the criterion includes evaluating a condition associated with the firstrisk score. The server 104 communicates the first risk score to the useron the user device 102 if the criterion is not met. If the criterion ismet, the server 104 determines the second risk score for thegeographical location to improve the accuracy of the first risk score.To determine the second risk score, the server 104 performs a second setof geospatial operations on the second file to extract the second datafrom the memory. The second set of geospatial operations may include,but are not limited to, the PIP operation, the DTL operation, the DTPoperation, the DTT operation, and the DTD operation. The second dataincludes information associated with the geographical location and thehazard such as the risk values, the distances between the geographicallocations and geospatial elements, and the like. The server 104determines the second risk score based on the second data and the secondset of rules associated with the hazard. In the example, the criterionincludes checking if the first risk score is ‘A’ or ‘B’, i.e., thegeographical location is more than 20 miles from the coast. If thecriterion is not met, i.e., if the first risk score is not ‘A’ or ‘B’,the server 104 communicates the first risk score, for example ‘D’, tothe user on the user device 102. If the criterion is met, the server 104performs a PIP operation on the second file to determine if thegeographical location is in the tsunami zone. The server 104 determinesthe second risk score based on a result of the PIP operation, and thesecond set of rules that are associated with the hazard ‘tsunami’. Theresult of the PIP operation, i.e., the second data indicates if thegeographical location is located inside the tsunami zone. The second setof rules dictate that if the first risk score is ‘A’ or ‘B’ and thegeographical location is located inside the tsunami zone, the secondrisk score is ‘C’. The server 104 further communicates the second riskscore to the user by way of the user device 102.

In another embodiment, if the criterion is not met, the server 104determines a third risk score based on third data extracted from thethird file and the third set of rules associated with the hazard thatare retrieved from the memory. The server 104 further communicates thethird risk score to the user on the user device 102. It will be apparentto a person skilled in the art that a method for determination of thethird risk score is same as the determination of the first and secondrisk scores.

Thus, in the present invention, the risk score associated with thegeographical location is not predetermined. On the contrary, the riskscores, such as the first through third risk scores are determinedon-the-fly. Further, the present invention relies on more than onefactor, in the example, distance of the geographical location from thecoast line and presence of the geographical location in the tsunamizone, to improve the accuracy of hazard risk assessment. It will beapparent to a person skilled in the art that the server 104 maydetermine additional risk scores other than the first through third riskscores, for assessment of hazard risks. The server 104 furthercommunicates the additional risk scores to the user by way of the userdevice 102.

It will be apparent to a person skilled in the art the server 104performs the aforementioned steps to identify corresponding risk scoresassociated with the hazards ‘fire’ and ‘crime’. It will further beapparent to a person skilled in the art that the server 104 providesthree risk scores as a final risk score that correspond to tsunami,fire, and crime, to the user on the user device 102.

It will be understood by those skilled in the art that the examplesprovided in the present invention are for clarity of understanding andshould not be considered as the only implementation of the presentinvention. Hence, the factors described in the examples may change.Similarly, the sequence of factors may vary. It will also be apparent tothose skilled in the art that the number of factors is not restricted totwo and the server 104 may consider more than two factors fordetermination of hazard risk scores.

Referring now to FIG. 2, a block diagram that illustrates variouscomponents of the user device 102 and the server 104, in accordance withan embodiment of the present invention. The user device 102 includescircuitry, such as a first processor 202, a first transceiver 204, afirst memory 206, a display 208 that is capable of rendering a graphicaluser interface (GUI) such as a user interface 210, and a firstinput/output (I/O) port 212 that communicate with each other by way of afirst communication bus 214. The server 104 includes circuitry, such asa second processor 216, a second transceiver 218, the memory of theserver 104, i.e., a second memory 220, and a second I/O port 222 thatcommunicate with each other by way of a second communication bus 224.

The first processor 202 includes suitable logic, circuitry, and/orinterfaces that are operable to execute instructions stored in the firstmemory 206 to perform multiple operations. For example, the firstprocessor 202 transmits the information associated with the geographicallocation to the second processor 216 by way of the first transceiver 204over the communication network 106. In an embodiment, the firstprocessor 202 receives the address or the geographical position from theuser. In another embodiment, the first processor 202 captures andtransmits Global Positioning Services (GPS) information of the userdevice 102 by means of one or more location-sensors (not shown) embeddedin the user device 102. In a scenario, when the information associatedwith the geographical location is an address, the first processor 202performs a geocoding operation to obtain the latitude and longitude ofthe geographical location and further transmits it to the secondprocessor 216. In another scenario, the second processor 216 performsthe geocoding operation.

The first processor 202 receives the risk score from the secondprocessor 216, and displays the risk score on the display 208. In anembodiment, the first processor 202 receives the risk score by way of aShort Message Service (SMS). Examples of the first processor 202include, but are not limited to, an application-specific integratedcircuit (ASIC) processor, a reduced instruction set computing (RISC)processor, a complex instruction set computing (CISC) processor, or afield-programmable gate array (FPGA). It will be apparent to a personskilled in the art that the first processor 202 is compatible withmultiple operating systems. It will further be apparent to a personskilled in the art that the first processor 202 may be compatible withmultiple displays, for example, the display 208.

The first transceiver 204 includes suitable logic, circuitry, and/orinterfaces that are operable to transmit (or receive) data to (or from)various devices, such as the second transceiver 218 over thecommunication network 106. For example, the first transceiver 204transmits the information associated with the geographical locationprovided by the user by means of the first I/O port 212 or received bythe first processor 202 by means of the one or more location-sensors(not shown) embedded in the user device 102, to the second transceiver218 over the communication network 106. The first transceiver 204receives the risk score, from the second transceiver 218 over thecommunication network 106. Examples of the first transceiver 204include, but are not limited to, an antenna, a radio frequencytransceiver, a wireless transceiver, and a Bluetooth transceiver. Thefirst transceiver 204 communicates with the communication network 106,the first processor 202, and the second transceiver 218 using variouswired and wireless communication protocols, such as TCP/IP (TransmissionControl Protocol/Internet Protocol), UDP (User Datagram Protocol),2^(nd) Generation (2G), 3^(rd) Generation (3G), 4^(th) Generation (4G)communication protocols, or any combination thereof.

The first memory 206 includes suitable logic, circuitry, and/orinterfaces to store the instructions that are executed by the firstprocessor 202 to perform the multiple operations. The first memory 206stores location information of one or more geographical locations. Thefirst memory 206 further stores the risk score. Examples of the firstmemory 206 include, but are not limited to, a random-access memory(RAM), a read-only memory (ROM), a programmable ROM (PROM), and anerasable PROM (EPROM).

The display 208 includes suitable logic, circuitry, and/or interfacesthat are operable to execute the instructions stored in the first memory206 to perform multiple operations. The display 208 displays the serviceapplication or the web page based on the input provided by the user. Thedisplay 208 further displays the risk score. Examples of the display 208include, but are not limited to, a Resistive Touchscreen Liquid CrystalDisplay (LCD), a thin-film transistor (TFT) LCD, an in-plane switchingLCD, a Capacitive Touchscreen LCD, an Organic Light Emitting Diode(OLED), an Active-Matrix Organic Light Emitting Diode (AMOLED), a SuperAMOLED, a Retina Display, and a Haptic/Tactile touchscreen.

The first I/O port 212 includes suitable logic, circuitry, and/orinterfaces that are operable to execute the instructions stored in thefirst memory 206 to perform multiple operations. The first I/O port 212may include input and output devices that are configured to operateunder the control of the first processor 202 by way of the firstcommunication bus 214. By means of the first I/O port 212, the userprovides inputs to perform the multiple operations. For example, theuser may provide inputs to open the service application or the web pageon the user device 102, provide the information associated with thegeographical location, and the like. Examples of the input devices mayinclude a universal serial bus (USB) port, an Ethernet port, a real orvirtual keyboard, a mouse, a joystick, a touch screen, a stylus, amicrophone, and the like. Examples of the output devices may include thedisplay 208, a speaker, headphones, a universal serial bus (USB) port,an Ethernet port, and the like.

The second processor 216 includes suitable logic, circuitry, and/orinterfaces that are operable to execute instructions stored in thesecond memory 220 to perform multiple operations. For example, thesecond processor 216 receives the information associated with thegeographical location from the first transceiver 204. In response to thereceived information, the second processor 216 retrieves the historicalhazard data to identify the hazard associated with the geographicallocation from the second memory 220. Thus, the second processor 216initiates the assessment of hazard risks on-the-fly, i.e., after itreceives the information associated with the geographical location fromthe first transceiver 204. The second processor 216 further retrievesthe set of files associated with the identified hazard from the secondmemory 220. The second processor 216 further retrieves the first andsecond sets of rules from the second memory 220. It will be apparent toa person skilled in the art that the second processor 216 identifiesmore than one hazard associated with the geographical location andretrieves corresponding files associated with the hazard.

The second processor 216 further performs the first set of geospatialoperations on the first file and extracts the first data from the secondmemory 220 based on the first set of geospatial operations. The secondprocessor 216 determines the first risk score based on the first dataand the first set of rules associated with the hazard. The secondprocessor 216 further initiates the criterion. In an embodiment, if thecriterion is unmet, the second processor 216 transmits the first riskscore to the first processor 202 by means of the second transceiver 218.If the criterion is met, the second processor 216 performs the secondset of geospatial operations on the second file and extracts the seconddata from the second memory 220 based on the second set of geospatialoperations. The second processor 216 determines the second risk scorebased on the second data and the second set of rules associated with thehazard. The second processor 216 transmits the second risk score to thefirst processor 202 by means of the second transceiver 218. In anotherembodiment, if the criterion is unmet, the second processor 216determines the third risk score based on the third data extracted thatis from the third file, and the third set of rules retrieved from thesecond memory 220. The second processor 216 further communicates thethird risk score to the user on the user device 102. Examples of thesecond processor 216 include, but are not limited to, an ASIC processor,a RISC processor, a CISC processor, and a FPGA. It will be apparent to aperson skilled in the art that the second processor 216 is compatiblewith multiple operating systems.

The second transceiver 218 includes suitable logic, circuitry, and/orinterfaces that are operable to transmit (or receive) data to (or from)various devices, such as the first transceiver 204 over thecommunication network 106. For example, the second transceiver 218receives the information associated with the geographical location, fromthe first transceiver 204. The second transceiver 218 transmits the riskscore, to the first transceiver 204 over the communication network 106.Examples of the second transceiver 218 include, but are not limited to,an antenna, a radio frequency transceiver, a wireless transceiver, and aBluetooth transceiver. The second transceiver 218 communicates with thecommunication network 106, the second processor 216, and the firsttransceiver 204 using various wired and wireless communicationprotocols, such as TCP/IP, UDP, 2G, 3G, 4G communication protocols, orany combination thereof.

The second memory 220 includes suitable logic, circuitry, and/orinterfaces to store the instructions that are executed by the secondprocessor 216 to perform the multiple operations. The second memory 220manages and stores information associated with the geographicallocations and the corresponding hazards. The second memory 220 storesthe historical hazard data and the set of files. In an embodiment, thesecond memory 220 receives the historical hazard data and the sets offiles associated with the hazard from a global database or a regionaldatabase. The second memory 220 further stores the data associated withthe set of files, such as the first through third data. The dataincludes attributes such as distance to nearest polygon, distance topoint, distance to line, and the like. The second memory 220 furtherstores the sets of rules associated with the hazard, such as the firstthrough third sets of rules. In an embodiment, the second memory 220 isnot a part of the server 104 but implemented as a database server.Examples of the second memory 220 include, but are not limited to, aRAM, a ROM, a PROM, and an EPROM.

The second I/O port 222 includes suitable logic, circuitry, and/orinterfaces that are operable to execute the instructions stored in thesecond memory 220 to perform multiple operations. The second I/O port222 may include various input and output devices that are configured tooperate under the control of the second processor 216 by way of thesecond communication bus 224. For example, by means of the second I/Oport 222, an administrator associated with the server 104 providesinputs to perform the multiple operations. Examples of the input devicesmay include a universal serial bus (USB) port, an Ethernet port, a realor virtual keyboard, a mouse, a joystick, a touch screen, a stylus, amicrophone, and the like. Examples of the output devices may include adisplay screen, a speaker, headphones, a universal serial bus (USB)port, an Ethernet port, and the like.

FIGS. 3A and 3B collectively are flow charts that illustrate a methodfor assessing a hazard risk associated with a geographical location, inaccordance with an embodiment of the present invention. At step 302, thesecond processor 216 receives the information associated with thegeographical location by way of the second transceiver 218 over thecommunication network 106. The information includes the address of thegeographical location or the geographical position, i.e., latitude andlongitude of the geographical location. In an embodiment, the userinputs details including an address or a geographical position. Inanother embodiment, the address of the geographical location is receivedby the server 104 based on GPS information transmitted by the userdevice 102 over the communication network 106. In an example, the userprovides a geographical location ‘X’.

At step 304, the second processor 216 identifies the hazard based onhistorical hazard data stored in the second memory 220 with thegeographical location. When the second processor 216 receives thegeographical location from the user, it retrieves the historical hazarddata associated with the geographical location from the second memory220. The second processor 216 identifies the hazard based on thehistorical hazard data. In the example, the historical hazard dataincludes records of robbery, aggravated assault, burglary, and the likeassociated with the geographical location ‘X’. Thus, the secondprocessor 216 identifies the hazard as ‘crime’ associated with thegeographical location ‘X’.

At step 306, the second processor 216 retrieves the set of filesassociated with the identified hazard from the second memory 220. Thesecond processor 216 further retrieves the first and second sets ofrules associated with the hazard from the second memory 220. In theexample, the second processor 216 retrieves a set of files associatedwith the hazard ‘crime’.

At step 308, the second processor 216 performs the first set ofgeospatial operations on the first file. It will be apparent to a personskilled in the art that the second processor 216 performs the first setof geospatial operations on multiple files. Based on the first set ofgeospatial operations, the second processor 216 extracts the first datafrom the second memory 220. In the example, a geographical area ‘Y’ thatincludes the geographical location ‘X’ is divided into multiplepolygons. The first file thus includes the polygons, and the secondmemory 220 stores risk values associated with each polygon. A risk valuemay include a numeric value that indicates a preliminary risk associatedwith each polygon. The second processor 216 performs the first set ofgeospatial operations, i.e., the PIP operation to identify a polygon inwhich the geographical location ‘X’ lies. Based on the PIP operation,the second processor 216 extracts the risk value associated with thepolygon from the second memory 220.

At step 310, the second processor 216 determines the first risk scorebased on the first data and the first set of rules. In the example, thesecond processor 216 determines the first risk score based on theextracted risk value and the first set of rules. The first set of rulesdictate that if the extracted risk value is less than a firstpredetermined value, the geographical location ‘X’ is least likely to beaffected by the hazard ‘crime’. It will be apparent to a person skilledin the art that the first set of rules further dictates when thegeographical location ‘X’ is moderately likely or most likely to beaffected by the hazard ‘crime’.

At step 312, the second processor 216 initiates the criterion and checksif the criterion is met. In the example, the criterion includesconsideration of an additional factor such as distance between thegeographical location ‘X’ and the polygons that are adjacent to thepolygon that includes the geographical location ‘X’. If the criterion ismet, step 314 is executed. If the criterion is not met, step 318 isexecuted.

At step 314 the second processor 216 performs the second set ofgeospatial operations on the second file, to improve the accuracy ofhazard risk assessment. It will be apparent to a person skilled in theart that the second processor 216 performs the second set of geospatialoperations on multiple files. Based on the second set of geospatialoperations, the second processor 216 extracts the second data from thesecond memory 220. Based on the second data and the second set of rules,the second processor 216 determines the second risk score. In theexample, the second processor 216 performs the DTL operation todetermine the distances between the geographical location ‘X’ and thepolygons that are adjacent to the polygon that includes the geographicallocation ‘X’. The second processor 216 determines the number of polygonsthat are within a predetermined distance, in an example 1500 feet of thegeographical location ‘X’. The second processor 216 performs multiplePIP operations to extract the risk values of the polygons. The secondprocessor 216 determines a mathematical average of the risk scores thatinclude the first risk score and intermediate risk scores. Theintermediate risk scores are determined based on corresponding extractedrisk values and the first set of rules. Based on the mathematicalaverage and the second set of rules, the second processor 216 determinesthe second risk score. The second set of rules dictate that if themathematical average is less than a second predetermined value, thegeographical location ‘X’ is least likely to be affected by the hazard‘crime’. It will be apparent to a person skilled in the art that thesecond set of rules further dictates when the geographical location ‘X’is fairly likely or most likely to be affected by the hazard ‘crime’.

At step 316, the second processor 216 communicates the second risk scoreto the user by transmitting the second risk score to the user device102.

At step 318, the second processor 216 communicates the first risk scoreto the user by transmitting the first risk score to the user device 102.In another embodiment, when the criterion is not met, the secondprocessor 216 determines the third risk score based on the third datathat is extracted from the third file and the third set of rulesassociated with the hazard that are retrieved from the second memory220. The second processor 216 further communicates the third risk scoreto the user by transmitting the third risk score to the user device 102.Thus, the method determines the first through third risk scoreson-the-fly and does not rely on predetermined risk scores. The variousexamples of the method of FIGS. 3A and 3B have been described in detailin conjunction with FIGS. 4-6.

FIGS. 4A and 4B collectively are flow charts that illustrate a methodfor assessing a flood risk associated with a geographical location, inaccordance with an embodiment of the present invention. At step 402, thesecond processor 216 receives information associated with thegeographical location by way of the second transceiver 218 over thecommunication network 106.

At step 404, the second processor 216 identifies ‘flood’ as the hazardbased on historical hazard data stored in the second memory 220 with thegeographical location. The historical hazard data includes records offloods occurred across a country, for example a country ‘J’ thatincludes the geographical location, and level of damages caused by eachflood. It will be apparent to a person skilled in the art that thesecond processor 216 identifies additional hazards associated with thegeographical location.

At step 406, the second processor 216 retrieves the set of files fromthe second memory 220 based on the hazard ‘flood’. The set of filesinclude information related to the hazard ‘flood’ that enables thesecond processor 216 to determine a risk score for the geographicallocation.

At step 408, the second processor 216 determines the first risk scorebased on the first set of geospatial operations. The second processor216 performs the PIP operation on the first file to identify a polygonin which the geographical location is located. The first file includes ageographical area in the form of polygons and each polygon indicates aflood risk associated with the polygon. The second memory 220 stores therisk value associated with each polygon. The second processor 216extracts the first data, i.e., the risk value of the polygon from thesecond memory 220. In one embodiment, the second processor 216 extractsthe first data from the first file to determine the first risk score. Inan embodiment, the extracted first data is the first risk score. Inanother embodiment, the second processor 216 performs a predeterminedoperation on the extracted first data to determine the first risk score.

At step 410, the second processor 216 initiates the criterion to checkif the first risk score is ‘C’ or ‘D’. The first risk score of ‘C’ or‘D’ signifies that the geographical location is moderately or morelikely to be affected by the hazard ‘flood’. If the first risk score is‘C’ or ‘D’, step 412 is executed. If the first risk score is not ‘C’ or‘D’, step 418 is executed.

At step 412, the second data, i.e., a distance of the geographicallocation to a nearest polygon with a risk score of ‘F’ (highest riskscore) is determined. The second processor 216 performs the DTL or theDTP operation on the first file to determine the distance. In anotherembodiment, the second processor 216 performs the DTL or DTP operationon the second file to determine the distance.

At step 414, the second processor 216 determines the second risk scorebased on the second data and the second set of rules associated with thehazard ‘flood’ retrieved from the second memory 220. The set of rulesdictates that if the distance is less than 100 feet, the second riskscore is an ‘F’. Further if the distance is more than or equal to 100feet, the second risk score is same as the first risk score.

At step 416, the second processor 216 communicates the second risk scoreto the user by transmitting the second risk score to the user device102.

At step 418, the second processor 216 communicates the first risk scoreto the user by transmitting the first risk score to the user device 102.For example, the second processor 216 communicates the first risk scoreto the user when the first risk score is one of an ‘A’, a ‘B’, or an‘F’.

FIG. 5 is a flow chart that illustrates a method for assessing the floodrisk associated with a geographical location, in accordance with anotherembodiment of the present invention. At step 502, the second processor216 receives the information associated with the geographical locationby way of the second transceiver 218 over the communication network 106.The information includes an address of the geographical location or thegeographical position, i.e., latitude and longitude of the geographicallocation.

At step 504, the second processor 216 identifies ‘flood’ as the hazardbased on the historical hazard data stored in the second memory 220 withthe geographical location.

At step 506, the second processor 216 retrieves the set of filesassociated with the hazard ‘flood’ from the second memory 220. The setof files include information such as ‘distance’ and ‘elevation’ of thegeographical location to water bodies such as streams, lakes, and pondsthat enables the second processor 216 to determine a risk score for thegeographical location associated with the hazard ‘flood’. The secondprocessor 216 further retrieves the first and second sets of rules thatare associated with the hazard ‘flood’ from the second memory 220. In anexample, a first file includes a set of stream lines, a second fileincludes a set of stream polygons, and a third file includes a set oflake and pond polygons.

At step 508, the second processor 216 performs the DTL operation on thefirst file to determine a first distance between the geographicallocation and a stream line. The second processor 216 performs the DTPoperation on the second and third files to determine second and thirddistances between the geographical location and stream polygons and lakeand pond polygons, respectively.

At step 510, the second processor 216 determines corresponding firstrisk scores for the first through third files, respectively, based onthe first through third distances and the first set of rules. In anexample, the first set of rules dictate that the geographical locationsthat are close to the stream polygon, i.e., within 1000 feet, areassigned a higher risk score, such as ‘D’ or ‘F’ and the geographicallocations that are far from the stream polygon, i.e., more than 3000feet, are assigned a lower risk score, such as ‘A’ or ‘B’. Similarly,the first set of rules dictate the determination of the first riskscores associated with the stream line and lake and pond polygons.

At step 512, the second processor 216 initiates the criterion todetermine the second data, i.e., first through third elevationdifferences, between the geographical location and the stream line,stream polygon, and lake and pond polygons, respectively.

At step 514, the second processor 216 determines the correspondingsecond risk scores based on the first through third distances and thefirst through third elevation differences. The second processor 216 usesthe second set of rules to determine the corresponding second riskscores. In an example, the second set of rules dictate that thegeographical location having a lower first risk score, such as an ‘A’ ora ‘B’ associated with the stream polygon may be affected by the hazard‘flood’ occurring in the stream polygon if the corresponding elevationdifference is within 20 feet. Hence, the risk score associated with thestream polygon for the geographical location is no longer an ‘A’ or a‘B’ but is adjusted to a ‘D’ or an ‘F’ to provide accuracy in the hazard‘flood’ risk assessment. The adjusted risk score is the second riskscore associated with the stream polygon. Similarly, the second set ofrules dictate the determination of the second risk scores associatedwith the stream line and lake and pond polygons. Thus, the correspondingsecond risk scores indicate the level of flood risk associated with thestream line, stream polygon, and lake and pond polygons, respectively.

At step 516, the second processor 216 selects one risk score from thesecond risk scores. In an embodiment, the second processor 216 selectsthe risk score with a highest risk level of the three second riskscores. In an example, if the second risk scores associated with thestream line, the stream polygon, and the lake and pond polygons are ‘C’,‘F’, and ‘D’, respectively, the second processor 216 selects risk scorewith highest risk level, i.e., ‘F’ as the second risk score.

At step 518, the second processor 216 communicates the selected secondrisk score to the user by transmitting the selected second risk score tothe user device 102.

FIGS. 6A, 6B, and 6C collectively are flow charts that illustrate amethod for assessing a wildfire risk associated with a geographicallocation, in accordance with an embodiment of the present invention. Atstep 602, the second processor 216 receives information associated withthe geographical location by way of the second transceiver 218 over thecommunication network 106. The information includes an address of thegeographical location or the geographical position, i.e., latitude andlongitude of the geographical location.

At step 604, the second processor 216 identifies ‘wildfire’ as thehazard based on historical hazard data stored in the second memory 220for the geographical location. For example, when the second processor216 receives a geographical location ‘Z’ which is in the geographicalarea ‘L’, the second processor 216 retrieves the historical hazard dataassociated with the geographical location ‘Z’ and the geographical area‘L’. The historical hazard data includes accounts of wildfire with thegeographical location ‘Z’ and the geographical area ‘L’. Based on thehistorical hazard data, the second processor 216 identifies ‘wildfire’as one of the hazard associated with the geographical location ‘Z’. Itwill be apparent to a person skilled in the art that the secondprocessor 216 further retrieves additional historical hazard data toidentify corresponding hazards associated with the geographical location‘Z’.

At step 606, the second processor 216 retrieves the set of filesassociated with the hazard ‘wildfire’ from the second memory 220. In theexample, the set of files include information related to the hazard‘wildfire’ such as a wildland fuel load, an urban or wildland interface,and housing density that enables the second processor 216 to determine arisk score for the geographical location ‘Z’ associated with the hazard‘wildfire’. The second processor 216 further retrieves the first andsecond sets of rules that are associated with the hazard ‘wildfire’ fromthe second memory 220.

At step 608, the second processor 216 performs the PIP operation on thefirst file to identify a first polygon in which the geographicallocation is located. The second processor 216 extracts the first data,i.e., the risk value of the first polygon, from the second memory 220.In one embodiment, the second processor 216 extracts the first data fromthe first file. The second processor 216 determines the first risk scorebased on the first data. In an embodiment, the extracted risk value isthe first risk score. In another embodiment, the second processor 216performs a predetermined operation on the extracted risk value todetermine the first risk score.

At step 610, the second processor 216 performs the PIP operation on thesecond file to initiate a first criterion, i.e., check an averagerainfall. The second file includes multiple polygons and the secondmemory 220 stores the average rainfall in the geographical areaassociated with each polygon. Based on a result of the PIP operation,the second processor 216 determines a second polygon in which thegeographical location is located. The second processor 216 extracts theaverage rainfall of the second polygon from the second memory 220. Thedetermination of average rainfall improves the risk assessment for thehazard ‘wildfire’.

At step 612, the second processor 216 checks if the geographicallocation is a humid region based on a value of the average rainfall. Ifthe geographical location is a humid region, step 626 is executed. Ifthe geographical location ‘Z’ is not a humid region, step 614 isexecuted.

At step 614, the second processor 216 checks if the geographicallocation is an arid region based on the value of the average rainfall.If the geographical location is an arid region, step 616 is executed. Ifthe geographical location is not an arid region, step 624 is executed.

At step 616, the second processor 216 initiates a second criterion,i.e., checks if the first risk score is ‘A’, ‘B’, or ‘C’. If the firstrisk score is ‘A’, ‘B’, or ‘C’, step 618 is executed. If the first riskscore is not ‘A’, ‘B’, or ‘C’, step 624 is executed.

At step 618, the second processor 216 performs the DTL or the DTPoperation on the second file to determine the second data, i.e., adistance of the geographical location to the nearest polygon that has arisk score of ‘D’ or ‘F’. In another embodiment, the second processor216 performs the DTL or the DTP operation on the third file to determinethe distance of the geographical location to the nearest polygon withthe risk score of ‘D’ or ‘F’.

At step 620, the second processor 216 determines the second risk scorebased on the second data and the first set of rules. The first set ofrules dictate that if the distance of the geographical location to thenearest polygon that has a risk score of ‘D’ or ‘F’ is less than 1000feet, the second risk score is ‘D’ or ‘F’. The first set of rulesfurther dictate that if the distance is more than or equal to 1000 feet,the second risk score is same as the first risk score.

At step 622, the second processor 216 communicates the second risk scoreto the user by transmitting the second risk score to the user device102.

At step 624, the second processor 216 communicates the first risk scoreto the user by transmitting the first risk score, for example ‘D’, tothe user device 102.

At step 626, the second processor 216 adjusts the first risk score to athird risk score since the geographical location is in the humid region.In an embodiment, the third risk score has a higher risk level than thefirst risk score.

At step 628, the second processor 216 initiates a third criterion, i.e.,checks if the geographical location lies in a drought polygon. A fourthfile includes multiple drought polygons indicating drought zones.

At step 630, the second processor 216 performs the PIP operation on thefourth file to determine if the geographical location is located in adrought polygon. The second processor 216 checks the result of the PIPoperation to determine if the geographical location is located in thedrought polygon. If the geographical location is located in the droughtpolygon, step 632 is executed. If the geographical location is notlocated in the drought polygon, step 636 is executed.

At step 632, the second processor 216 determines a fourth risk scorebased on the third risk score and the second set of rules. The secondset of rules dictate that the geographical location that lies in adrought region may be affected by the hazard ‘wildfire’ even if itsfirst risk score indicates that it is less likely to be affected. Hence,the risk score for the geographical location ‘Z’ is adjusted to provideaccuracy in the hazard risk assessment.

At step 634, the second processor 216 communicates the fourth risk scoreto the user by transmitting the fourth risk score to the user device102.

At step 636, the second processor 216 communicates the third risk scoreto the user by transmitting the third risk score to the user device 102.

Referring now to FIG. 7, a block diagram that illustrates a computersystem 700 for assessing the hazard risks associated with thegeographical locations, in accordance with an embodiment of the presentinvention. An embodiment of the present invention, or portions thereof,may be implemented as computer readable code on the computer system 700.In one example, the server 104 of FIG. 1 may be implemented as thecomputer system 700 using hardware, software, firmware, non-transitorycomputer readable media having instructions stored thereon, or acombination thereof and may be implemented as one or more computersystems or other processing systems. Hardware, software, or anycombination thereof may embody modules and components used to implementthe methods of FIGS. 3-3B, 4A-4B, 5, and 6A-6C.

The computer system 700 includes a processor 702 that may be a specialpurpose or a general-purpose processing device. The processor 702 may bea single processor, multiple processors, or combinations thereof. Theprocessor 702 may have one or more processor “cores.” Further, theprocessor 702 may be connected to a communication infrastructure 704,such as a bus, a bridge, a message queue, the communication network 106,multi-core message-passing scheme, and the like. The computer system 700further includes a main memory 706 and a secondary memory 708. Examplesof the main memory 706 may include a random-access memory (RAM), aread-only memory (ROM), and the like. The secondary memory 708 mayinclude a hard disk drive or a removable storage drive (not shown), suchas a floppy disk drive, a magnetic tape drive, a compact disc, anoptical disk drive, a flash memory, and the like. Further, the removablestorage drive may read from and/or write to a removable storage devicein a manner known in the art. In an embodiment, the removable storageunit may be a non-transitory computer readable recording media.

The computer system 700 further includes an input/output (I/O) port 710and a communication interface 712. The I/O port 710 includes variousinput and output devices that are configured to communicate with theprocessor 702. Examples of the input devices may include a keyboard, amouse, a joystick, a touchscreen, a microphone, and the like. Examplesof the output devices may include a display screen, a speaker,headphones, and the like. The communication interface 712 may beconfigured to allow data to be transferred between the computer system700 and various devices that are communicatively coupled to the computersystem 700. Examples of the communication interface 712 may include amodem, a network interface, i.e., an Ethernet card, a communicationsport, and the like. Data transferred via the communication interface 712may be signals, such as electronic, electromagnetic, optical, or othersignals as will be apparent to a person skilled in the art. The signalsmay travel via a communications channel, such as the communicationnetwork 106 which may be configured to transmit the signals to thevarious devices that are communicatively coupled to the computer system700. Examples of the communication channel may include, but are notlimited to, cable, fiber optics, a phone line, a cellular phone link, aradio frequency link, a wireless link, and the like.

Computer program medium and computer usable medium may refer tomemories, such as the main memory 706 and the secondary memory 708,which may be a semiconductor memory such as dynamic RAMs. These computerprogram mediums may provide data that enables the computer system 700 toimplement the methods illustrated in FIGS. 3A-3B, 4A-4B, 5, and 6A-6C.In an embodiment, the present invention is implemented using a computerimplemented application. The computer implemented application may bestored in a computer program product and loaded into the computer system700 using the removable storage drive or the hard disc drive in thesecondary memory 708, the I/O port 710, or the communication interface712.

A person having ordinary skill in the art will appreciate thatembodiments of the disclosed subject matter may be practiced withvarious computer system configurations, including multi-coremultiprocessor systems, minicomputers, mainframe computers, computerslinked or clustered with distributed functions, as well as pervasive orminiature computers that may be embedded into virtually any device. Forinstance, at least one processor, such as the processor 702, and amemory, such as the main memory 706 and the secondary memory 708,implement the above described embodiments. Further, the operations maybe described as a sequential process; however some of the operations mayin fact be performed in parallel, concurrently, and/or in a distributedenvironment, and with program code stored locally or remotely for accessby single or multiprocessor machines. In addition, in some embodiments,the order of operations may be rearranged without departing from thespirit of the disclosed subject matter.

Specific advantages of the method and the system for assessing thehazard risks include use of more than one factor for determination ofthe risk score. The additional factors ensure that various conditionsrelated to the hazard risk are thoroughly considered and the determinedrisk scores are fairly accurate. The risk scores associated with thegeographical location are not predetermined. On the contrary, the methodand the system determine the risk scores on-the-fly, i.e., dynamically,and do not provide the risk scores to the user that are determinedbeforehand, as done by traditional methods of hazard risk assessment.The method and the system eliminate the need for rebuilding a geospatialfile for reflecting any updates in the risk scores. A user may utilizethe risk score in renting or buying a property, insurance policypricing, insurance underwriting, reinsurance underwriting, suggestionsfor necessary mitigations, buying decisions, siting decisions, managingportfolio determinations, and the like. Thus, the method and the systemovercome the disadvantages of the traditional methods for assessing thehazard risks associated with the geographical locations.

Techniques consistent with the present invention provide, among otherfeatures, systems and methods for assessing the hazard risks associatedwith the geographical locations. Unless stated otherwise, terms such as“first” and “second” are used to arbitrarily distinguish between theelements such terms describe. Thus, these terms are not necessarilyintended to indicate temporal or other prioritization of such elements.While various exemplary embodiments of the disclosed system and methodhave been described above it should be understood that they have beenpresented for purposes of example only, not limitations. It is notexhaustive and does not limit the invention to the precise formdisclosed. Modifications and variations are possible in light of theabove teachings or may be acquired from practicing of the invention,without departing from the breadth or scope.

1. A method for assessing hazard risks associated with geographical locations, the method comprising: receiving, by a server, information associated with a geographical location; identifying, by the server, a hazard that is associated with the geographical location based on historical hazard data; retrieving, by the server, one or more files associated with the hazard; determining, by the server, a first risk score for the geographical location based on at least the one or more files or a first set of rules associated with the hazard; determining, by the server, a second risk score for the geographical location based on at least the one or more files or a second set of rules associated with the hazard, wherein the second risk score is determined when a criterion associated with the hazard is met; and communicating, by the server, at least one of the first risk score or the second risk score associated with the geographical location to a user, wherein the first risk score and the second risk score indicate a level of severity of the hazard for the geographical location.
 2. The method of claim 1, wherein the information includes at least an address or a geographical position of the geographical location.
 3. The method of claim 2, wherein the information is received from a user device.
 4. The method of claim 1, wherein the server retrieves the historical hazard data and the one or more files from a memory.
 5. The method of claim 1, wherein the hazard includes at least one of a flood, a coastal storm surge, a tsunami, a wildfire, a damaging wind, a hailstorm, a tornado, lightning strikes, a hurricane, an earthquake, a fracking induced earthquake, radiations from radioactive zones and nuclear power plants, wind borne debris, a landslide, a lava flow, brownfield or superfund sites, leaking of underground storage tanks, a crime, volcanic eruptions, or any other natural or man-made hazards.
 6. The method of claim 1, wherein the one or more files include a plurality of geospatial elements.
 7. The method of claim 6, wherein the plurality of geospatial elements includes at least lines, points, polygons, or raster cells.
 8. The method of claim 1, wherein the criterion associated with the hazard is based on at least the first risk score or the one or more files.
 9. The method of claim 1, wherein the server communicates the first risk score to the user when the criterion associated with the hazard is unmet and communicates the second risk score to the user when the criterion associated with the hazard is met.
 10. The method of claim 1, further comprising determining, by the server, a third risk score for the geographical location based on at least the one or more files or a third set of rules associated with the hazard, wherein the third risk score is determined when the criterion associated with the hazard is unmet.
 11. A system for assessing hazard risks associated with geographical locations, the system comprising: a server configured to: receive information associated with a geographical location; identify a hazard that is associated with the geographical location based on historical hazard data; retrieve one or more files associated with the hazard; determine a first risk score for the geographical location based on at least the one or more files or a first set of rules associated with the hazard; determine a second risk score for the geographical location based on at least the one or more files or a second set of rules associated with the hazard, wherein the second risk score is determined when a criterion associated with the hazard is met; and communicate at least one of the first risk score or the second risk score associated with the geographical location to a user, wherein the first risk score and the second risk score indicate a level of severity of the hazard for the geographical location.
 12. The system of claim 10, wherein the information includes at least an address or a geographical position of the geographical location.
 13. The system of claim 11, wherein the information is received from a user device.
 14. The system of claim 10, wherein the server retrieves the historical hazard data and the one or more files from a memory.
 15. The system of claim 10, wherein the hazard includes at least one of a flood, a coastal storm surge, a tsunami, a wildfire, a damaging wind, a hailstorm, a tornado, lightning strikes, a hurricane, an earthquake, a fracking induced earthquake, radiations from radioactive zones and nuclear power plants, wind borne debris, a landslide, a lava flow, brownfield or superfund sites, leaking of underground storage tanks, a crime, volcanic eruptions, or any other natural or man-made hazards.
 16. The system of claim 10, wherein the one or more files include a plurality of geospatial elements.
 17. The system of claim 16, wherein the plurality of geospatial elements includes at least lines, points, polygons, or raster cells.
 18. The system of claim 10, wherein the criterion associated with the hazard is based on at least the first risk score or the one or more files.
 19. The system of claim 10, wherein the server communicates the first risk score to the user when the criterion associated with the hazard is unmet and communicates the second risk score to the user when the criterion associated with the hazard is met.
 20. The system of claim 10, wherein the server is further configured to determine a third risk score for the geographical location based on at least the one or more files or a third set of rules associated with the hazard, and wherein the third risk score is determined when the criterion associated with the hazard is unmet. 